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  <div class="section" id="numpy-count-nonzero">
<h1>numpy.count_nonzero<a class="headerlink" href="#numpy-count-nonzero" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="numpy.count_nonzero">
<code class="sig-prename descclassname">numpy.</code><code class="sig-name descname">count_nonzero</code><span class="sig-paren">(</span><em class="sig-param">a</em>, <em class="sig-param">axis=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/v1.18.1/numpy/core/numeric.py#L402-L462"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#numpy.count_nonzero" title="Permalink to this definition">¶</a></dt>
<dd><p>Counts the number of non-zero values in the array <code class="docutils literal notranslate"><span class="pre">a</span></code>.</p>
<p>The word “non-zero” is in reference to the Python 2.x
built-in method <code class="docutils literal notranslate"><span class="pre">__nonzero__()</span></code> (renamed <code class="docutils literal notranslate"><span class="pre">__bool__()</span></code>
in Python 3.x) of Python objects that tests an object’s
“truthfulness”. For example, any number is considered
truthful if it is nonzero, whereas any string is considered
truthful if it is not the empty string. Thus, this function
(recursively) counts how many elements in <code class="docutils literal notranslate"><span class="pre">a</span></code> (and in
sub-arrays thereof) have their <code class="docutils literal notranslate"><span class="pre">__nonzero__()</span></code> or <code class="docutils literal notranslate"><span class="pre">__bool__()</span></code>
method evaluated to <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p>
<dl class="field-list">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl>
<dt><strong>a</strong><span class="classifier">array_like</span></dt><dd><p>The array for which to count non-zeros.</p>
</dd>
<dt><strong>axis</strong><span class="classifier">int or tuple, optional</span></dt><dd><p>Axis or tuple of axes along which to count non-zeros.
Default is None, meaning that non-zeros will be counted
along a flattened version of <code class="docutils literal notranslate"><span class="pre">a</span></code>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.12.0.</span></p>
</div>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><strong>count</strong><span class="classifier">int or array of int</span></dt><dd><p>Number of non-zero values in the array along a given axis.
Otherwise, the total number of non-zero values in the array
is returned.</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="numpy.nonzero.html#numpy.nonzero" title="numpy.nonzero"><code class="xref py py-obj docutils literal notranslate"><span class="pre">nonzero</span></code></a></dt><dd><p>Return the coordinates of all the non-zero values.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="mi">4</span><span class="p">))</span>
<span class="go">4</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">([[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">],[</span><span class="mi">3</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">19</span><span class="p">]])</span>
<span class="go">5</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">([[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">],[</span><span class="mi">3</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">19</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="go">array([1, 1, 1, 1, 1])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">([[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">],[</span><span class="mi">3</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">19</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="go">array([2, 3])</span>
</pre></div>
</div>
</dd></dl>

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